Even handheld computing devices such as mobile phones and tablets now demand high-resolution, high-color displays, thus requiring high-wattage backlight lamps and large-capacity frame buffer memories which together lead to high power consumption. The frame buffer, the area of memory that stores fragments of data during rasterization of an image on a display, is a big consumer of both memory bandwidth and storage space, and this can put adversely impact the memory subsystem of a graphics processing unit (GPU). In addition, together with the display backlight, frame buffers consume a significant percentage of a device's power. Particularly in mobile devices with limited battery life, frame buffer power consumption can present significant challenges in light of the high refresh rate, resolution, and color depth of displays. Thus, reducing frame buffer activity helps to extend overall battery life.
Accordingly, frame buffer compression (FBC) is becoming increasingly popular for rendering images on the displays of high-resolution mobile phone and tablet devices. This applies both to regular panels, where FBC can reduce the required link rate, as well as to smart panels, where FBC can reduce both the link rate and panel memory requirement, saving cost. Some approaches to FBC can reduce the number of accesses to the frame buffer, thereby reducing power costs. The power consumption of the frame buffer and its associated buses is proportional to the number of frame buffer accesses during rasterization. The number of accesses is in turn determined by the screen resolution, the refresh rate, and the color depth. Power consumption of the frame buffer is also inversely proportional to the compression ratio.
As display size and resolution continues to increase, there is increased demand for higher compression ratios in frame buffer compression. Even as the demands on compression FBC techniques increase, the requirements of FBC continue to be (1) low-complexity, in that the driver integrated circuit of the mobile device can implement compression and decompression with limited computational resources, (2) visually lossless quality, in that the user should not see any visual degradation in the image due to compression and decompression, and (3) a fixed compression rate.